Cost-effectiveness of intracranial pressure monitoring in severe traumatic brain injury in Southern Thailand

Jidapa Jitchanvichai; Thara Tunthanathip

doi:10.4266/acc.004080

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Original Article Neurosurgery Cost-effectiveness of intracranial pressure monitoring in severe traumatic brain injury in Southern Thailand: Jidapa Jitchanvichai, Thara Tunthanathip; Acute and Critical Care 2025;40(1):69-78.
DOI: https://doi.org/10.4266/acc.004080
Published online: February 21, 2025

Division of Neurosurgery, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand

Corresponding author: Thara Tunthanathip Division of Neurosurgery, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand Tel: +66-92-5495994 Fax: +66-74-429384 Email: tsus4@hotmail.com

• Received: October 21, 2024 • Revised: November 22, 2024 • Accepted: December 29, 2024

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
KEY MESSAGES
NOTES
SUPPLEMENTARY MATERIALS
REFERENCES

Abstract

Background
Traumatic brain injury (TBI) is a leading cause of fatalities and disabilities in the public health domain, particularly in Thailand. Guidelines for TBI patients advise intracranial pressure monitoring (ICPm) for intensive care. However, information about the cost-effectiveness (CE) of ICPm in cases of severe TBI is lacking. This study assessed the CE of ICPm in severe TBI.
Methods
This was a retrospective cohort economic evaluation study from the perspective of the healthcare system. Direct costs were sourced from electronic medical records, and quality-adjusted life years (QALY) for each individual were computed using multiple linear regression with standardization. Incremental costs, incremental QALY, and the incremental CE ratio (ICER) were estimated, and the bootstrap method with 1,000 iterations was used in uncertainty analysis.
Results
The analysis included 821 individuals, with 4.1% undergoing intraparenchymal ICPm. The average cost of hospitalization was United States dollar ($)8,697.13 (±6,271.26) in both groups. The incremental cost and incremental QALY of the ICPm group compared with the non-ICPm group were $3,322.88 and –0.070, with the base-case ICER of $–47,504.08 per additional QALY. Results demonstrated that 0.007% of bootstrapped ICERs were below the willingness-to-pay (WTP) threshold of Thailand.
Conclusions
ICPm for severe TBI was not cost-effective compared with the WTP threshold of Thailand. Resource allocation for TBI prognosis requires further development of cost-effective treatment guidelines.
Key Words: cost-effectiveness analysis; craniocerebral trauma; health economics; intracranial pressure; intracranial hypertension

INTRODUCTION

Traumatic brain injury (TBI) is one of the leading causes of fatalities and disabilities in the public health domain, particularly in Thailand [1,2]. The in-hospital mortality rates for individuals with TBI demonstrate significant variation ranging from 4.0% to 35.3% [3,4]. Previous studies found that the mortality rate of severe TBI ranged from 46.0% to 96.7%, while mortality rates of mild and moderate TBI patients were 3.5%–7.0% and 4.2%–13.0%, respectively [5-7].

For Glasgow Coma Scale (GCS) scores <9, intracranial pressure monitoring (ICPm) is advised due to the association between intracranial pressure >22 mm Hg and mortality [5,6]. However, the impact of ICPm on mortality remains controversial [8,9]. The impact of ICPm in severe TBI cases was investigated using propensity score matching (PSM) by Alali et al. [10] and Rønning et al. [11], with results indicating that ICPm was linked to an increase in in-hospital mortality. Conversely, Barami et al. [12] performed ICPm in severe TBI patients and found that ICPm did not impact in-patient mortality and long-term outcomes, while two other studies recorded no survival benefit among patients under ICPm [13,14].

The economic costs of hospitalization for TBI patients vary. The median expense of hospitalization in Europe was €3,800, €37,800, and €60,400 for mild, moderate, and severe TBI, respectively [15], while hospitalization costs for TBI patients in the United States averaged United States dollar ($)21,460±21,212 [16]. A few investigations have calculated the cost-effectiveness (CE) of ICPm in severe TBI [17]. Zapata-Vázquez et al. [16] performed an economic evaluation of ICPm in children with severe TBI using a decision tree model. They found that the incremental CE ratio (ICER) was Mex$81,062, and 54% of cost-effective iterations exceeded the willingness-to-pay (WTP) threshold of Mex$500,000. As a result, they determined that ICPm was cost-effective due to a financial advantage shown in incremental net monetary benefits [16].

ICPm was previously not covered by Thai public health insurance schemes, but is now universally covered for emergency patients [15,16]. There have been few reports on the CE of ICPm in severe cases of TBI in Thailand [18,19]. This study assessed the CE of ICPm in severe TBI in Thailand.

MATERIALS AND METHODS

The Human Research Ethics Committee of the Faculty of Medicine, Prince of Songkla University, Thailand approved the study (REC.66-201-10-1). Informed consent was not necessary for this retrospective study. However, patient identification numbers were encoded prior to analysis.

Study Design and Study Population

This was a retrospective cohort economic evaluation study from the perspective of the healthcare system. The study population was initially gathered in a prior study by Jitchanvichai and Tunthanathip [14]. The inclusion criteria were individuals with a GCS score of less than 9 at the emergency department of a tertiary referral hospital in southern Thailand between January 2014 and January 2023. Exclusion criteria were patients who died before being admitted to the hospital or in the emergency department, who did not undergo preoperative cranial computed tomography (CT), or whose medical records were not available. In addition, patients who underwent ICPm through ventriculostomy (intraventricular ICPm) and different types of ICPm such as subdural ICPm were also excluded. The demographic data, mechanism of injury, laboratory tests, treatment, cost, and outcome were collected from the electronic medical database of our hospital. The type of cerebral injuries, midline shift, and patency of the basal cistern were evaluated on imaging by two neurosurgeons.

ICP Monitoring

The study population was divided into ICPm and non-ICPm groups based on treatment, and both treatment groups underwent standard management. Patients with severe TBI were admitted to the surgical intensive care unit (ICU) or neuro-trauma ICU if ICU wards were available. Patients in both groups underwent intubation, intravenous fluid infusion for maintaining euvolemia, hyperosmolar therapy, normothermia maintenance, reassessment of neurological status and serial cranial CT scans. In our institution, there was no consensus on ICPm indication; however, neurosurgeon preferences in the present study were based on the 2007 and 2016 Brain Trauma Foundation guidelines [20,21]. For the ICPm procedure, a microsensor catheter was inserted into the intraparenchyma in the frontal area (Codman Microsensor ICP Transducer, Integra LifeSciences Holdings Corp.); then, ICP was continuously measured by ICPm system (Codman ICP Express).

Statistical Analysis

Descriptive statistics were used to identify clinical factors and imaging findings, with categorical data reported as percentages, while mean values with standard deviation were analyzed in continuous variables. The standardized mean difference (SMD) was calculated to assess an imbalance in clinical characteristics between ICPm and non-ICPm groups. An SMD of 0.1 or more indicates an imbalance of clinical characteristics between groups [14]. The PSM approach was performed to adjust the imbalance of covariates. In detail, the propensity score was created from all covariates that had SMD 0.1 or more; therefore, exact matching with a 1:1 ratio procedure was done. Hence, a covariate balance plot was created to visualize SMD before and after matching. Descriptive statistics and PSM analyses were carried out with R version 4.4.0 (R Foundation).

The direct medical costs including medical services, medication, surgical procedures, treating physician service, laboratory testing, and imaging were collected from the hospital database. Following the guidelines for health technology assessment in Thailand, a ratio of cost to charge (RCC) value of 1.63 was used to convert charge to cost [22,23] as follows:

Cost=RCC × charge

This was a retrospective study; therefore, the monetary value was converted from past to present using the consumer price index (CPI) value for medical care in January of each year from the Ministry of Commerce, Thailand [22,23] as follows:

Present monetary value=cost ×CPIpresentCPIpast

All costs were calculated as the monetary values in 2024 and converted to United States dollars (1 Thai Baht equaled 0.030 United States Dollars on September 14, 2024). For treatment outcome, quality-adjusted life years (QALY) for each TBI patient were computed based on multiple linear regression following Tunthanathip et al. [24] as follows:

QALY= −0.302+0.102 pupillary light reflex+0.009 Glasgow Coma Scale−0.039 surgery+0.230 Glasgow Outcome Scale

QALY results were standardized in the range 0 to 1 before the CE analysis [25,26]. The ICER revealed an additional cost per unit of QALY if the treatment was guided by ICPm as follows:

ICER= CostICPm−CostNo ICPmQALYICPm− QALYNo ICPm

Therefore, the base case ICER and confidence ellipses of 50%, 75%, and 95% were estimated and shown in the CE plane [27]. In detail, the CE plane is divided into four quadrants as follows: top-right quadrant, top-left quadrant, bottom-left quadrant, and bottom-right quadrant. The top-right quadrant implies that the ICPm group has higher costs but higher QALY, whereas the top-left quadrant indicates that the ICPm group has higher costs and poorer outcomes. The bottom-right quadrant represents lower costs and better outcomes for the ICPm group, and the bottom-left quadrant, lower costs and inferior outcomes. Furthermore, the WTP threshold determines the CE of ICPm. If the ICER was below the WTP threshold line in the CE plane, the ICPm was considered cost-effective. The WTP threshold in Thailand was used as a fixed value at $4,813.48 per additional QALY, while the WTP thresholds of the US were between $50,000 and $100,000 per additional QALY [28].

For uncertainty analysis, one-way sensitivity analysis and a bootstrap method were used in the present study. A tornado diagram was employed for sensitivity analysis, which shows how much a certain covariate affects ICER. In addition, a bootstrap method with 1,000 iterations was performed and bootstrap ICERs were plotted in the incremental CE plane against various WTP thresholds. The percentage of bootstrap ICERs under the WTP indicated the proportion of CE of ICPm [29]. All statistical analyses were performed using Stata version 16 (StataCorp.; SN 401606310234).

RESULTS

A total of 849 patients with severe TBI were included in the study, with 28 individuals eliminated based on the exclusion criteria. Twenty individuals died before arrival, four patients died in the emergency department, and one did not undergo cranial CT. Additionally, three patients were excluded because they underwent intraventricular ICPm, as shown in Figure 1. Baseline clinical characteristics by treatment are shown in Table 1. The average age of the non-ICP monitoring group was 37.41 years (±19.52), whereas the ICPm group had a mean age of 30.79 years (±18.62). The most common mechanism of injury in both groups was a motorcycle collision, with posttraumatic seizure rates ranging from 5.7% to 5.9%, and the most common radiological finding was subdural hematoma. The average midline shift of the non-ICPm group was 3.31 (±5.47), whereas the ICPm group had a mean midline shift of 1.41 (±3.57). Based on the 6-month Glasgow Outcome Scale (GOS), the mortality rate was found to be 23.5% in the ICPm group and 30.5% in the non-ICPm group. Several covariates had a SMD of 0.1 or more that indicated an imbalance of characteristics as follows: age, GCS, hypotension, pupillary light reflex, contusion, diffuse axonal injury (DAI), obliterated basal cistern, and midline shift.

The propensity score was calculated using imbalance covariates, and the density of propensity scores by treatment group is presented in Figure 1. To correct for the covariate imbalance, PSM with a 1:1 ratio was performed. Figure 2 shows the covariate balance plot that compares the balance of patient characteristics between the two treatment groups before and after matching. After PSM, all imbalance covariates had a SMD of less than 0.1. Baseline clinical characteristics by treatment after PSM are presented in the Supplementary Table 1.

CE Analysis

The average cost of hospitalization was $8,697.13 (±6,271.26) in both groups. Table 2 shows the costs, duration of hospital stay, and standardized QALY. The average overall cost of the ICPm group was substantially greater than that of the non-ICPm group, and these costs comprised medical equipment, diagnostic imaging, nursing care, and operating expenses. The ICPm group had a substantially longer length of hospital stay and admission in the ICU than the non-ICPm group. The average QALY of the non-ICPm group was 0.492 (±0.340), whereas the ICPm group had a mean QALY of 0.422 (+0.256). The CE analysis framework suggested that the incremental costs and incremental QALY of the ICPm group compared with the non-ICPm group were US$3322.88 and –0.070, with a base-case ICER of $–47,504.08 per additional QALY (Table 3).

Uncertainty Analysis

The base-case ICER with 95%, 75%, and 50% ellipses was placed in the CE plane, as shown in Figure 3A. The base-case ICER is in the upper-left quadrant, indicating that ICPm costs more and produces poorer results. Furthermore, the base-case ICER above the WTP threshold line demonstrated that ICPm was not cost-effective at Thailand's WTP threshold. Using bootstrapping techniques, uncertainty analysis was conducted. Figure 3B shows the bootstrapped ICERs in the CE plane, with most placed in the upper-left quadrant, indicating that ICPm was more expensive and less effective. Seven of the 1,000 bootstrapped ICER values were under the WTP threshold, implying that ICP monitoring would be cost-effective in 0.007% of such cases in Thailand. When the bootstrapped ICERs were assessed using the United States WTP levels of $50,000 to $100,000 per increased QALY, results showed 6.1% and 10.6% cost effectiveness, respectively.

For one-way sensitivity analysis, the tornado chart is shown in Figure 4. The horizontal bars represent how much the ICER changes in percentage when each covariate is adjusted between its lower and upper bounds. The results showed that DAI, 6-month GOS, and pupillary light reflex were the covariates with the greatest influence on the ICER.

DISCUSSION

The results showed that the ICPm group had a considerably greater overall cost than the control group. This was explained by the higher cost of intervention and length of ICU stay. The number of patients in the ICPm group was less than in the control group because the cost of ICPm led to a personal economic burden [14,30]. Therefore, neurosurgeons typically managed patients based on imaging and clinical evaluation without ICPm [19,31]. In the real-world data, an imbalance in patients' clinical characteristics was observed. PSM is a typical method of adjusting for covariate imbalance in observational research [14,32]. Prior research utilized propensity score analysis to evaluate the impact of ICP monitoring on hospital mortality; however, there is a lack of PSM analysis in health economic studies. Hence, the present study adjusted for imbalanced variables before to CE analysis. For CE analysis, results indicated that ICPm was not cost-effective, even when different WTP levels were used. Zapata-Vázquez et al. [16] reported an ICER of Mex$81,062 and an incremental cost for the ICPm of Mex$3,934 using a simulation modeling technique. Furthermore, the present study's base-case and bootstrap ICERs were compared to WTP thresholds from previous studies conducted in Southeast Asia ($9,000 for a Malaysian study and $36,500 for a Singapore study) [33,34]. The CE analysis results were consistent with the WTP threshold from Thailand.

The results of the decision tree model indicated that ICPm was cost-effective. However, evidence of economic evaluation for ICPm intervention was limited, and further research is needed to confirm CE results. The high cost of ICPm restricts the availability of this technique. Guidelines should be developed to determine which patients are most likely to benefit from resource allocation [30]. Choosing patients with a better prognosis will enhance CE and help establish treatment plans in practical settings [31,35,36]. Various clinical prediction tools for severe TBI have been investigated, such as scoring systems, nomograms, and machine learning algorithms, that can help optimize resource allocation strategies and guidelines [4,35,37,38].

To the best of our knowledge, this is the first study to assess the CE of ICPm results in Thailand. However, this study had some limitations. In this retrospective cohort study, the QALY of each individual were determined using multiple linear regression with standardization. Health-related quality of life measures collected directly from an individual are more accurate than a statistical method. However, several prior studies proposed this approach for QALY prediction from a literature review [26,29,38]. Sun et al. [26] employed regression models to predict postoperative QALY compared to the 36-item short form survey (SF-36) questionnaire in patients following bariatric surgery, with favorable outcomes. Furthermore, because these patients frequently have cognitive impairments and reduced consciousness, assessing QALY in severe TBI patients is often difficult [24]. Our study used input data collected on an individual level, which resulted in limited generalizability [39,40]. Economic studies should employ available parameters to indicate an individual's economic gains; therefore, we assessed the currently available economic models using the study parameters. Alternatively, a pooled effect of ICPm based on a systematic review and meta-analysis should be conducted to improve model-based CE analyses because currently, evidence that ICPm diminishes the mortality rate among TBI patients remains controversial. ICPm for TBI patients was shown not to be cost-effective and results from real-world data should be used to facilitate better clinical decision-making and resource allocation by physicians and policymakers. Alternative neuromonitoring technologies that may have better clinical results or CE, such as jugular venous oxygen saturation monitoring or brain tissue oxygen tension monitoring, should be investigated.

In summary, ICPm for severe TBI was not cost-effective based on Thailand’s WTP threshold. Prognosis or severity-based resource allocation for TBI requires further research to establish effective and cost-effective treatment guidelines.

KEY MESSAGES

▪ In severe traumatic brain injury (TBI), continuous intracranial pressure monitoring (ICPm) is recommended.

▪ Thai public health insurance schemes did not previously cover ICPm; however, it is now universally covered for emergency patients.

▪ There have been a limited number of reports on the cost-effectiveness of ICPm in severe cases of TBI in Thailand.

▪ Educational workshops for intensive care unit nurses are needed to introduce the recommended guidelines and teach nurses about the benefits of low tidal ventilation.

▪ In comparison to Thailand's willingness-to-pay threshold, ICPm for severe TBI was not cost-effective.

NOTES

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

None.

ACKNOWLEDGMENTS

The study population data were sourced from research by Jitchanvichai et al. [14]. This study focused mainly on the cost-effectiveness of intracranial pressure monitoring.

AUTHOR CONTRIBUTIONS

Conceptualization: all authors. Methodology: all authors. Formal analysis: TT. Data curation: all authors. Visualization: TT. Project administration: TT. Writing - original draft: all authors. Writing - review & editing: TT. All authors read and agreed to the published version of the manuscript.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.4266/acc.004080.

Supplementary Table 1.

Clinical characteristics of study population by treatment after propensity score matching

acc-004080-Supplementary-Table-1.pdf

Figure 1.

Patient selection flowchart. TBI: traumatic brain injury; GCS: Glasgow Coma Scale; CT: computed tomography.

Figure 2.

Propensity score matching for covariate balance adjustment. (A) Density of propensity scores for the no intracranial pressure (ICP) monitoring and ICP monitoring groups. (B) Covariate balance plot showing standardized mean difference of each covariate before and after matching with a standardized mean difference at 0.1 (dashed line). GCS: Glasgow Coma Scale; ER: emergency room; IVH: intraventricular hemorrhage; SSS: social security scheme; CSMBS: Civil Service Medical Benefits Scheme; SAH: subarachnoid hemorrhage; OE: one eye; SDH: subdural hematoma; DAI: diffuse axonal injury; BE: both eyes; EDH: epidural hematoma; UCS: universal coverage scheme; MLS: midline shift.

Figure 3.

Base-case and bootstrap incremental cost-effectiveness ratios (ICERs) in the cost-effectiveness plane. (A) Base-case ICER and confidence ellipses of 50%, 75%, and 95%. (B) Bootstrap ICERs with various willingness-to-pay (WTP) thresholds. US: United States.

Figure 4.

Tornado diagram of one-way sensitivity analysis. ICER: incremental cost-effectiveness ratios; DAI: diffuse axonal injury; GOS: Glasgow Outcome Scale; GCS: Glasgow Coma Scale; ER: emergency room; EDH: epidural hematoma; SDH: subdural hematoma; IVH: intraventricular hemorrhage; SAH: subarachnoid hemorrhage.

Table 1.

Baseline clinical characteristics of study population by treatment (n=821)

Factor	Treatment		SMD^a)
Factor	No ICP monitoring	ICP monitoring
Number	787	34
Sex
Male	622 (79.0)	28 (82.4)	0.04
Female	165 (21.0)	6 (17.6)	0.03
Mean age (yr)	37±20	31±19	0.34^a)
Age group (yr)
<60	677 (86.0)	31 (91.2)	0.01
≥60	110 (14.0)	3 (8.8)	0.02
Medical benefits scheme
Universal coverage scheme	478 (60.7)	22 (64.7)	0.03
Civil servant medical benefit scheme	129 (16.4)	6 (17.6)	0.01
Social security scheme	127 (16.1)	5 (14.7)	0.06
Self-payment	15 (1.9)	1 (2.9)	0.01
GCS score at emergency room	5.6±1.9	5.4±1.7	0.10^a)
Road traffic accident	610 (77.5)	28 (82.4)	0.04
Aspirin usage	11 (1.4)	1 (2.9)	0.01
Clopidogrel	7 (0.9)	0	0.01
Warfarin	5 (0.6)	0	0.01
Thrombocytopenia	2 (0.3)	0	0.002
Seizure	45 (5.7)	2 (5.9)	0.001
Hypotension	116 (14.7)	1 (2.9)	0.11^a)
Bradycardia	16 (2.0)	0	0.02
Pupillary light reflex
Fixed both eyes	148 (18.8)	4 (11.8)	0.07
React one eyes	148 (18.8)	13 (38.2)	0.16^a)
React both eyes	491 (62.4)	17 (50.0)	0.14^a)
Blood alcoholic level (mg%)	70.5±104.8	58.8±109.2	0.05
Skull fracture	124 (15.8)	2 (5.9)	0.09
EDH	136 (17.3)	7 (20.6)	0.03
SDH	450 (57.2)	20 (58.8)	0.01
Contusion	317 (40.3)	20 (58.8)	0.18^a)
SAH	355 (45.1)	17 (50.0)	0.04
IVH	129 (16.4)	7 (20.6)	0.04
DAI	83 (10.5)	13 (38.2)	0.27^a)
Brainstem hematoma	18 (2.3)	2 (5.9)	0.03
Obliterated basal cistern	269 (34.2)	6 (17.6)	0.16^a)
Midline shift (mm)	3.3±5.5	1.4±3.6	0.41^a)
6-Month Glasgow Outcome Scale
Death	240 (30.5)	8 (23.5)	0.06
Vegetative state	154 (19.6)	10 (29.4)	0.09
Severe disability	127 (16.1)	8 (23.5)	0.07
Moderate disability	125 (15.9)	7 (20.6)	0.04
Good recovery	141 (17.9)	1 (2.9)	0.03

Values are presented as number (%) or mean±standard deviation.

ICP: intracranial pressure monitoring; SMD: standardized mean difference; GCS: Glasgow Coma Scale; EDH: epidural hematoma; SDH: subdural hematoma; SAH: subarachnoid hemorrhage; IVH: intraventricular hemorrhage; DAI: diffuse axonal injury.

^a)SMD ≥0.1 indicates imbalance of covariate distribution between treatment groups.

Table 2.

Average cost, hospital stay, and QALY by treatment

Factor	No ICP monitoring	ICP monitoring	P-value^a)
Cost ($)
Total cost per admission	7,035.69±5,726.15	10,358.58±6,434.63	0.03
Medical equipment	174.16±333.95	1,216.19±770.32	<0.001
Drug	1,231.63±2,139.27	1,180.46±1,083.24	0.90
Laboratory	484.57±729.04	598.88±401.25	0.43
Diagnostic radiology	1,202.17±698.64	1,532.80±721.01	0.06
Nursing care	469.41±391.60	687.33±609.37	0.09
Rehabilitation	46.62±76.18	55.08±102.76	0.70
Surgery	642.28±802.71	1,442.20±1,227.25	0.003
ICP equipment	-	709.67±299.53	-
Length of ICU stay (day)	2.55±4.65	5.21±4.31	0.01
Length of hospital stay (day)	24.00±22.24	29.09±24.69	0.38
QALY	0.49±0.34	0.42±0.26	0.34

Values are presented as mean±standard deviation.

QALY: quality-adjusted life year; ICP: intracranial pressure; ICU: intensive care unit.

^a)t-test.

Table 3.

Incremental cost-effectiveness ratio results

Treatment	Cost ($)	Incremental cost ($)	QALY ($)	Incremental QALY ($)	Base-case ICER (95%CI)
ICP monitoring	10,358.58±6,434.63	3,322.88±1,499.42	0.42±0.26	–0.07±0.07	QALY –47,504.08
ICP monitoring	10,358.58±6,434.63	3,322.88±1,499.42	0.42±0.26	–0.07±0.07	(–5,746.88 to 21,229.31)
No ICP monitoring	7,035.69±5,726.15	-	0.49±0.34	-	-

Values are presented as mean±standard deviation.

QALY: quality-adjusted life year; ICER: incremental cost-effectiveness ratio; ICP: intracranial pressure.

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Cost-effectiveness of intracranial pressure monitoring in severe traumatic brain injury in Southern Thailand

Acute Crit Care. 2025;40(1):69-78. Published online February 21, 2025

DOI: https://doi.org/10.4266/acc.004080

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Figure

Cost-effectiveness of intracranial pressure monitoring in severe traumatic brain injury in Southern Thailand

Figure 1. Patient selection flowchart. TBI: traumatic brain injury; GCS: Glasgow Coma Scale; CT: computed tomography.

Figure 2. Propensity score matching for covariate balance adjustment. (A) Density of propensity scores for the no intracranial pressure (ICP) monitoring and ICP monitoring groups. (B) Covariate balance plot showing standardized mean difference of each covariate before and after matching with a standardized mean difference at 0.1 (dashed line). GCS: Glasgow Coma Scale; ER: emergency room; IVH: intraventricular hemorrhage; SSS: social security scheme; CSMBS: Civil Service Medical Benefits Scheme; SAH: subarachnoid hemorrhage; OE: one eye; SDH: subdural hematoma; DAI: diffuse axonal injury; BE: both eyes; EDH: epidural hematoma; UCS: universal coverage scheme; MLS: midline shift.

Figure 3. Base-case and bootstrap incremental cost-effectiveness ratios (ICERs) in the cost-effectiveness plane. (A) Base-case ICER and confidence ellipses of 50%, 75%, and 95%. (B) Bootstrap ICERs with various willingness-to-pay (WTP) thresholds. US: United States.

Figure 4. Tornado diagram of one-way sensitivity analysis. ICER: incremental cost-effectiveness ratios; DAI: diffuse axonal injury; GOS: Glasgow Outcome Scale; GCS: Glasgow Coma Scale; ER: emergency room; EDH: epidural hematoma; SDH: subdural hematoma; IVH: intraventricular hemorrhage; SAH: subarachnoid hemorrhage.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Cost-effectiveness of intracranial pressure monitoring in severe traumatic brain injury in Southern Thailand

Factor	Treatment		SMD^a)
Factor	No ICP monitoring	ICP monitoring
Number	787	34
Sex
Male	622 (79.0)	28 (82.4)	0.04
Female	165 (21.0)	6 (17.6)	0.03
Mean age (yr)	37±20	31±19	0.34^a)
Age group (yr)
<60	677 (86.0)	31 (91.2)	0.01
≥60	110 (14.0)	3 (8.8)	0.02
Medical benefits scheme
Universal coverage scheme	478 (60.7)	22 (64.7)	0.03
Civil servant medical benefit scheme	129 (16.4)	6 (17.6)	0.01
Social security scheme	127 (16.1)	5 (14.7)	0.06
Self-payment	15 (1.9)	1 (2.9)	0.01
GCS score at emergency room	5.6±1.9	5.4±1.7	0.10^a)
Road traffic accident	610 (77.5)	28 (82.4)	0.04
Aspirin usage	11 (1.4)	1 (2.9)	0.01
Clopidogrel	7 (0.9)	0	0.01
Warfarin	5 (0.6)	0	0.01
Thrombocytopenia	2 (0.3)	0	0.002
Seizure	45 (5.7)	2 (5.9)	0.001
Hypotension	116 (14.7)	1 (2.9)	0.11^a)
Bradycardia	16 (2.0)	0	0.02
Pupillary light reflex
Fixed both eyes	148 (18.8)	4 (11.8)	0.07
React one eyes	148 (18.8)	13 (38.2)	0.16^a)
React both eyes	491 (62.4)	17 (50.0)	0.14^a)
Blood alcoholic level (mg%)	70.5±104.8	58.8±109.2	0.05
Skull fracture	124 (15.8)	2 (5.9)	0.09
EDH	136 (17.3)	7 (20.6)	0.03
SDH	450 (57.2)	20 (58.8)	0.01
Contusion	317 (40.3)	20 (58.8)	0.18^a)
SAH	355 (45.1)	17 (50.0)	0.04
IVH	129 (16.4)	7 (20.6)	0.04
DAI	83 (10.5)	13 (38.2)	0.27^a)
Brainstem hematoma	18 (2.3)	2 (5.9)	0.03
Obliterated basal cistern	269 (34.2)	6 (17.6)	0.16^a)
Midline shift (mm)	3.3±5.5	1.4±3.6	0.41^a)
6-Month Glasgow Outcome Scale
Death	240 (30.5)	8 (23.5)	0.06
Vegetative state	154 (19.6)	10 (29.4)	0.09
Severe disability	127 (16.1)	8 (23.5)	0.07
Moderate disability	125 (15.9)	7 (20.6)	0.04
Good recovery	141 (17.9)	1 (2.9)	0.03

Factor	No ICP monitoring	ICP monitoring	P-value^a)
Cost ($)
Total cost per admission	7,035.69±5,726.15	10,358.58±6,434.63	0.03
Medical equipment	174.16±333.95	1,216.19±770.32	<0.001
Drug	1,231.63±2,139.27	1,180.46±1,083.24	0.90
Laboratory	484.57±729.04	598.88±401.25	0.43
Diagnostic radiology	1,202.17±698.64	1,532.80±721.01	0.06
Nursing care	469.41±391.60	687.33±609.37	0.09
Rehabilitation	46.62±76.18	55.08±102.76	0.70
Surgery	642.28±802.71	1,442.20±1,227.25	0.003
ICP equipment	-	709.67±299.53	-
Length of ICU stay (day)	2.55±4.65	5.21±4.31	0.01
Length of hospital stay (day)	24.00±22.24	29.09±24.69	0.38
QALY	0.49±0.34	0.42±0.26	0.34

Treatment	Cost ($)	Incremental cost ($)	QALY ($)	Incremental QALY ($)	Base-case ICER (95%CI)
ICP monitoring	10,358.58±6,434.63	3,322.88±1,499.42	0.42±0.26	–0.07±0.07	QALY –47,504.08
ICP monitoring	10,358.58±6,434.63	3,322.88±1,499.42	0.42±0.26	–0.07±0.07	(–5,746.88 to 21,229.31)
No ICP monitoring	7,035.69±5,726.15	-	0.49±0.34	-	-

Table 1. Baseline clinical characteristics of study population by treatment (n=821)

Values are presented as number (%) or mean±standard deviation.

SMD ≥0.1 indicates imbalance of covariate distribution between treatment groups.

Table 2. Average cost, hospital stay, and QALY by treatment

Values are presented as mean±standard deviation.

QALY: quality-adjusted life year; ICP: intracranial pressure; ICU: intensive care unit.

t-test.

Table 3. Incremental cost-effectiveness ratio results

Values are presented as mean±standard deviation.

QALY: quality-adjusted life year; ICER: incremental cost-effectiveness ratio; ICP: intracranial pressure.